基于异常事件驱动的簇结构的检测算法

An algorithm for abnormal event driven cluster topology detection

有效地使用传感节点能量,并提高检测异常事件概率,成为无线传感网络应用研究热点。为此,提出基于异常事件驱动的簇结构的检测算法(AEDCTD)。AEDCTD算法通过异常事件位置建立簇,然后由簇内节点检测事件。在建立簇时,考虑了节点对事件的检测概率及节点剩余能量,只有当剩余能量大于能量阈值的节点才可能加入簇。同时,引用动态能量阈值,平衡能耗。实验数据表明,AEDCTD算法具有较低的漏检率,同时,AEDCTD算法与CCM和GEP-ADS算法的能耗相比分别降低了近4.1%和5.8%。

Effective use of sensor node energy and improvement of abnormal event detection probability have become hot research spots in wireless sensor network application.Therefore,an algorithm for abnormal event driven cluster topology detection(AEDCTD)is proposed.In the AEDCTD algorithm,the cluster is constructed according to the positions of abnormal events,and events are detected by nodes in the cluster.During cluster construction,the event detection probability and residual energy of nodes are considered,and only the nodes whose residual energy is larger than the energy threshold can join the cluster.The dynamic energy threshold is introduced to balance energy consumption.The experimental results show that in compari?son with the CCM and GEP-ADS algorithms,the AEDCTD algorithm has lower missed detection probability,and can save ener?gy consumption of about 4.1%and 5.8%respectively.